US20190383950A1 - Method and arrangement for improving global positioning performance of a road vehicle - Google Patents
Method and arrangement for improving global positioning performance of a road vehicle Download PDFInfo
- Publication number
- US20190383950A1 US20190383950A1 US16/444,221 US201916444221A US2019383950A1 US 20190383950 A1 US20190383950 A1 US 20190383950A1 US 201916444221 A US201916444221 A US 201916444221A US 2019383950 A1 US2019383950 A1 US 2019383950A1
- Authority
- US
- United States
- Prior art keywords
- data
- global positioning
- road vehicle
- road
- vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/865—Combination of radar systems with lidar systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/867—Combination of radar systems with cameras
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/52—Determining velocity
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/9316—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles combined with communication equipment with other vehicles or with base stations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/9327—Sensor installation details
-
- G01S2013/936—
-
- G01S2013/9371—
Definitions
- the disclosure is related to a method and arrangement for improving global positioning performance of a road vehicle.
- Global positioning of an autonomous driving (AD) road vehicle is mainly based on positioning data such as Global Positioning System (GPS) coordinates.
- GPS Global Positioning System
- Such positioning data may not be very accurate and may differ from the actual global position of the road vehicle at a certain time.
- a more precise global positioning of the vehicle is critical and there is a need to develop approaches to address problems with inadequate global positioning accuracy.
- CN104502936 discloses a positioning and navigation system comprising a combined positioning unit, an intelligent ranging unit, a cloud communication unit and a vehicle-mounted display unit.
- the combined positioning unit is used for realizing real-time positioning of the vehicle; the intelligent ranging unit is used for realizing calculation on the distance between the vehicle and a surrounding target; and the cloud communication unit is used for receiving data generated by the combined positioning unit and the intelligent ranging unit and for uploading the data to a cloud service centre.
- the cloud service centre carries out map labelling on navigation positioning data, and the labelling information is issued to the vehicle-mounted display unit.
- DE102012224110 discloses a method and system for determining positioning data of an object on a road.
- An environmental sensor system e.g. camera, radar sensor
- the determined relative distances can serve as a filter basis, on the basis of which the positioning data of the object to be located can either be completely predetermined or, for example, specified in terms of tolerance.
- an object can determine its absolute geographical position using the absolute geographical position of the other object and the relative distances.
- An object may also determine the position of another other object if its own absolute geographical position but not the corresponding absolute geographical position of the other object is available.
- U.S. Pat. No. 9,933,268 is disclosed a digital map enhancement system for improving accuracy of pre-stored digital map data of a digital map to be utilized by a vehicle.
- the system determines a current position of the vehicle, and identifies, in the pre-stored digital map data, a mapped digital landmark representing a stationary landmark predicted to be in the vicinity of the current position of the vehicle, which mapped digital landmark includes a pre-stored position of the stationary landmark.
- the system detects the stationary landmark by one or more sensor devices on-board the vehicle, which are adapted for observing the surroundings of the vehicle, and determines a detected position of the stationary landmark based on the current position of the vehicle and the detection of the stationary landmark.
- the system updates the pre-stored position of the mapped digital landmark with the detected position of the stationary landmark.
- An object of the present invention is to provide a method for improving global positioning performance of a road vehicle using global positioning data and information from onboard sensors on the road vehicle and on at least two neighbouring road vehicles. Another objective is to provide an arrangement for improving global positioning performance of a road vehicle.
- a method for improving global positioning performance of a first road vehicle comprising, by means of a data server: acquiring data from onboard sensors arranged on the first road vehicle and on at least two neighbouring road vehicles, the data comprising data on relative positions and data on heading angle and velocity of the road vehicles, and acquiring global positioning data of at least two of the road vehicles; processing the global positioning data, the data, with corresponding timestamp, acquired from the onboard sensors, and a motion model for each of the first road vehicle and the at least two neighbouring road vehicles, using a data fusion algorithm; calculating adjusted global positioning data for the first road vehicle, and communicating the adjusted global positioning data to a positioning system of the first road vehicle.
- a road vehicle may be a car, a truck, a bus etc.
- the first road vehicle and the at least two neighbouring road vehicles may be different types of road vehicles or be the same type of road vehicle, e.g. cars.
- the road vehicles may be autonomous driving (AD) vehicles or vehicles with advanced driving assistance systems (ADAS) for measuring vehicle information and information about the vehicle surroundings.
- At least one of the vehicles may be an autonomous driving (AD) vehicle and the other vehicles with advanced driving assistance systems (ADAS).
- All vehicles may be AD vehicles.
- All vehicles may be vehicles with ADAS.
- a vehicle provided with ADAS is here a vehicle provided with systems to help a driver in the driving process, e.g.
- AD vehicles are vehicles that are capable of sensing their environment and to navigate without human input. AD vehicles may, hence, be controlled without human interaction. AD vehicles could range from fully automated to semi-automated vehicles.
- the number of neighbouring vehicles used in the method should be at least two.
- the number of vehicles in the method may vary and may depend on different factors such as the number of onboard sensors on the vehicles, strength of sensor signals, distance to neighbouring vehicles etc.
- the road vehicles used by the method may form a wireless network.
- the onboard sensors may be arranged to detect environmental information associated with the road vehicle. Such sensors may e.g. detect a location of the vehicle, a velocity of the vehicle, an orientation of the vehicle, heading angle of the vehicle, and a status of surroundings of the vehicle.
- the at least two neighbouring road vehicles are located in relation to the first road vehicle in an area close enough such that onboard sensors on the respective road vehicle may detect at least one other vehicle.
- the size of such an area depends on the sensor set up on each road vehicle and the sensor coverage.
- the time stamp is the time at which an event is recorded by an onboard sensor.
- a motion model for a road vehicle is here meant any vehicle motion model, e.g. a constant velocity model or a constant acceleration model.
- Each road vehicle may be provided with a data server communication unit for sending/receiving data to/from the data server.
- the global positioning data of a road vehicle may e.g. be Global Positioning System (GPS) coordinates. Such positioning data may not be very accurate and may differ from the actual global position at a certain time.
- GPS Global Positioning System
- the global positioning data received by the data server may be global positioning data for the first road vehicle and one or more neighbouring vehicles, or global positioning data for the at least two neighbouring vehicles only.
- sensors provide object information in different sampling periods.
- the sampling times are asynchronous.
- object dynamics e.g. position, velocity, heading angle, etc. at the same sampling period. This may be done using an asynchronous data fusion algorithm.
- a positioning system of a vehicle is a system arranged to adjust the positioning of the vehicle on the road based on the received adjusted global positioning data.
- the global positioning performance of a road vehicle may be improved.
- Using relative distances between vehicles (pseudo-ranges) results in a more accurate global positioning compared to pseudo-ranges calculated with respect to GPS satellites. As all vehicles are located in approximately the same plane, this improves the global positioning accuracy of a vehicle.
- the accurate positioning needed is in the longitudinal and latitudinal direction and as the pseudo-range calculated in the method is in this plane the positioning accuracy is improved compared to when using GPS coordinates alone.
- the present method is a cooperative vehicle global positioning method and each road vehicle may be seen as a moving anchor in a wireless network. Data that each road vehicle gathers about other vehicles is used to improve the global positioning. By this method, vehicles provided with ADAS may contribute for a more accurate global positioning of (an) AD vehicle(s).
- the data server may be located in the first road vehicle.
- the data server may comprise a central data server.
- the data server could be a central data server, e.g. a cloud.
- the cloud may include different modules for communication; receiving and sending data, storing data, and processing of data.
- the data server may comprise a data server located in at least one of the road vehicles and/or a central data server.
- the data server could comprise a distributed data server with a data server arranged in at least one or more of the road vehicles, such that there may be a full vehicle-to-vehicle (V2V) communication.
- V2V vehicle-to-vehicle
- the data server could be a distributed data server comprising a central data server (cloud) and (a) data server(s) located in at least one of the road vehicles, thereby reducing the amount of communication with the central data server. Some functions of the data server could then be performed by the central server and some functions by (a) data server(s) located in at least one of the vehicles. If one vehicle loses connection with the central server there may be a possibility to indirectly connect to the central server via another vehicle used in the method.
- An onboard sensor may be selected from a group comprising radars, vision sensors and lidar sensors.
- At least one of the road vehicles may be an autonomous driving (AD) vehicle.
- AD autonomous driving
- At least one of the road vehicles may be a vehicle with advanced driving assistance systems (ADAS).
- ADAS advanced driving assistance systems
- the global positioning data processed by the data server may comprise the global positioning data of the first road vehicle.
- the global positioning data processed by the data server may consist of global positioning data of at least two of the neighbouring road vehicles, wherein the velocity of the road vehicles and the relative positions of the road vehicles may be used as positioning anchors for the first road vehicle when processing the data in the data server.
- the global positioning data of the first road vehicle is missing, which may be the case if the GPS connection of the first road vehicle is lost for some reason, e.g. when driving through a tunnel.
- a positioning anchor is a known object with respect to which the first road vehicle finds its position.
- the satellites are anchors.
- Anchors might be moving or stationary, their positions might be known or unknown.
- Global positioning data of one or more neighbouring road vehicles may be processed with the other data in the data server and adjusted global positioning data for at least one of the one or more neighbouring road vehicles may be calculated and communicated to a positioning system of the neighbouring road vehicle(s).
- the method may further comprise, by means of the data server, to acquire data for a neighbouring road vehicle having no active onboard sensors from onboard sensors on at least two of the road vehicles, the data comprising vehicle identification data and data on heading angle and velocity of the road vehicle having no active onboard sensors, and to acquire global positioning data of at least the neighbouring road vehicle having no active onboard sensors.
- processing data in the data server processing also the global positioning data and the data, with corresponding time stamp, acquired from the onboard sensors for the neighbouring road vehicle having no active onboard sensors, and using the velocity of the neighbouring road vehicle having no active onboard sensors as a positioning anchor for the first road vehicle.
- That a road vehicle does not have active onboard sensors is here meant that the vehicle is not provided with any onboard sensors or that the onboard sensors on the vehicle are not in use or not functioning.
- neighbouring road vehicles having no active onboard sensors may contribute in the method of improving the global positioning of the first road vehicle.
- the velocity and heading angle for the road vehicle having no active onboard sensors may be obtained through odometry signals.
- Vehicle identification data for at least some of the other vehicles used in the method may be acquired by the data server together with the vehicle identification data of the vehicle having no active road sensors.
- the method may further comprise, by means of the data server, to acquire data for a neighbouring road vehicle having no active onboard sensors from onboard sensors on at least two of the road vehicles, the data comprising vehicle identification data and data on heading angle and velocity of the road vehicle having no active onboard sensors, and acquiring global positioning data of at least the neighbouring road vehicle having no active onboard sensors.
- processing data in the data server processing also the global positioning data and the data, with corresponding time stamp, acquired from the onboard sensors for the neighbouring road vehicle having no active onboard sensors. Adjusted global positioning data for the neighbouring road vehicle having no active onboard sensors may be calculated and communicated to a positioning system of the neighbouring road vehicle having no active onboard sensors.
- That a road vehicle does not have active onboard sensors is here meant that the vehicle is not provided with any onboard sensors or that the onboard sensors on the vehicle are not in use or not functioning.
- a road vehicle having no active onboard sensors but provided with positioning data sensor may be connected to the data server via the other road vehicles and be provided with adjusted positioning data from the data server.
- road vehicles having no active onboard sensors may be provided with adjusted positioning data which may be used to adjust the spatial position of the road vehicle.
- This method would improve navigation performance where the positioning performance is poor and bring more accurate connected safety features to vehicles without onboard sensors.
- the velocity and heading angle for the road vehicle having no active onboard sensors may be obtained through odometry signals.
- Vehicle identification data for at least some of the other vehicles used in the method may be acquired by the data server together with the vehicle identification data of the vehicle having no active road sensors. This to make sure that the correct vehicle receives the adjusted global positioning data.
- the vehicle identification data for a road vehicle having no active onboard sensors may be the license plate number.
- the vehicle identification data of a vehicle without active onboard sensors need to be unique for that vehicle.
- the global position of a road vehicle may be adjusted.
- Such positioning adjustment is the spatial position of the vehicle in the longitudinal and latitudinal direction.
- an arrangement for improving global positioning performance of a first road vehicle comprises a data server communication unit for communication with a data server, onboard sensors arranged on the first road vehicle and being arranged to determine data on relative positions and data on heading angle and velocity of one or more neighbouring road vehicles, the data server communication unit further being arranged to send the determined data, with corresponding time stamp, to the data server.
- a global positioning sensor is arranged on the first road vehicle, the data server communication unit further being arranged to send global positioning data of the first road vehicle to the data server, and a positioning system is arranged on the first road vehicle.
- the data server communication unit further is arranged to receive to the positioning system of the first road vehicle adjusted global positioning data for the first road vehicle, the adjusted global positioning data obtained using a data fusion algorithm, the data fusion algorithm arranged to process global positioning data from the first road vehicle and at least one or more neighbouring road vehicles, a motion model of each road vehicle, data on relative positions of each road vehicle, and data on heading angle and velocity of the road vehicles, to calculate the adjusted global positioning data for the first road vehicle.
- FIG. 1 illustrates an arrangement for improving global positioning performance of a first road vehicle using global positioning data and information from onboard sensors on the first road vehicle and on at least two neighbouring road vehicles.
- FIG. 2 schematically illustrates method steps of a method for improving global positioning performance of a first road vehicle.
- Global positioning of an autonomous driving (AD) road vehicle is mainly based on positioning data such as Global Positioning System (GPS) coordinates, which may not be very accurate and may differ from the actual global position of the road vehicle at a certain time.
- GPS Global Positioning System
- FIG. 1 is shown an arrangement for improving global positioning performance of a road vehicle 10 using global positioning data and information from onboard sensors 2 , 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g on the road vehicle 10 and on at least two neighbouring road vehicles 10 ′, 10 ′′, 10 ′′′.
- FIG. 2 is schematically illustrated a method for improving the global positioning performance of a road vehicle.
- the arrangement comprises a first road vehicle 10 and at least two neighbouring road vehicles 10 ′, 10 ′′, 10 ′′′, a data server 3 , 4 , 4 ′′ and onboard sensors 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g arranged on the first road vehicle 10 and on the at least two neighbouring road vehicles 10 ′, 10 ′′, 10 ′′′.
- the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′ may be autonomous driving (AD) vehicles or vehicles with advanced driving assistance systems (ADAS). At least one of the vehicles may be an autonomous driving (AD) vehicle and the other vehicles with advanced driving assistance systems (ADAS). All vehicles may be AD vehicles. All vehicles may be vehicles with ADAS.
- the onboard sensors 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g may be arranged to determine data on relative positions and data on heading angle and velocity of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′.
- the vision sensor may be a camera.
- the radars may be front, rear and side radars, blind spot radars, etc.
- the number of onboard sensors 2 a. 2 b, 2 c, 2 d, 2 e, 2 f, 2 g on a vehicle 10 , 10 ′, 10 ′′, 10 ′′′ may vary but should be at least one.
- the number of onboard sensors on a vehicle engaged in the method may vary and may vary over time.
- the data is sent, with corresponding time stamp, to the data server 3 , 4 , 4 ′′ via a data server communication unit 7 , 7 ′, 7 ′′, 7 ′′′ arranged in each vehicle.
- the data server may be a data server 4 located in the first road vehicle 10 .
- the data server may alternatively be a central data server 3 , i.e. a cloud.
- the data server may comprise one or more distributed data servers 4 , 4 ′′ located in at least one of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′ and/or a central data server 3 .
- Global positioning sensors 5 , 5 ′, 5 ′′, 5 ′′′ may be arranged on the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′.
- Global positioning data e.g. Global Positioning System (GPS) coordinates
- GPS Global Positioning System
- the global positioning data may comprise global positioning data of the first road vehicle 10 and of one or more of the neighbouring road vehicles 10 ′, 10 ′′, 10 ′′′.
- the global positioning data may consist of global positioning data of at least two of the neighbouring road vehicles 10 ′, 10 ′′, 10 ′′′ and no data for the first road vehicle 10 .
- the data server 3 , 4 , 4 ′′ may process the data and a motion model for each of the first road vehicle 10 and the at least two neighbouring vehicles 10 ′, 10 ′′, 10 ′′′ using a data fusion algorithm and calculate an adjusted global positioning data for the first road vehicle 10 .
- the adjusted global positioning data may be communicated to a positioning system 6 of the first road vehicle 10 .
- the positioning system 6 may be arranged to adjust the global positioning of the vehicle 10 on the road, improving the global positioning performance of the first road vehicle. Data that each road vehicle 10 , 10 ′, 10 ′′, 10 ′′′ gathers about other vehicles is, hence, used to improve the global positioning of the first road vehicle 10 and a more accurate global positioning of the first road vehicle 10 may be obtained.
- the first step is to, by means of the data server 3 , 4 , 4 ′′, acquire data 101 from the onboard sensors 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g arranged on the first road vehicle and on at least two neighbouring road vehicles, the data comprising data on relative positions and data on heading angle and velocity of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′, and to acquire global positioning data of at least two of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′.
- the data server 3 , 4 , 4 ′′ processes 102 the data comprising the global positioning data, the data, with corresponding timestamp, acquired from the onboard sensors 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g, and a motion model for each of the first road vehicle 10 and the at least two neighbouring road vehicles 10 ′, 10 ′′, 10 ′′′.
- adjusted global positioning data for the first road vehicle 10 is calculated 103 , and thereafter the adjusted global positioning data is communicated 104 to the positioning system 6 of the first road vehicle 10 .
- the global position of the first road vehicle may be adjusted 105 to a more accurate global position.
- global positioning data of the first road vehicle 10 may be missing. This situation may for example occur if the GPS connection of the first road vehicle 10 is lost for some reason, e.g. when driving through a tunnel.
- the global positioning data sent to the data server 3 , 4 , 4 ′′ then consists of global positioning data of at least two of the neighbouring vehicles 10 ′. 10 ′′, 10 ′′′.
- the velocity of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′ and relative positions of the road vehicles may in such a case be used as positioning anchors for the first road vehicle 10 when processing the data in the data server 3 , 4 , 4 ′′.
- the global positioning of a neighbouring road vehicle 10 ′ may be adjusted with this arrangement and method.
- Global positioning data of the one or more neighbouring road vehicles 10 ′ sent to the data server 3 , 4 , 4 ′′ may be processed together with the other data and adjusted global positioning data for the neighbouring road vehicle(s) 10 ′ communicated to (a) positioning system(s) 6 ′ of the neighbouring road vehicle(s) 10 ′.
- road vehicles having no onboard sensors may contribute in the method of improving the global positioning performance of the first road vehicle 10 .
- the data server 3 , 4 , 4 ′′ acquires data for a neighbouring road vehicle 10 IV having no active onboard sensors from onboard sensor(s) 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g on at least two of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′.
- the data comprising a unique vehicle identification data, e.g. license plate number, for at least that road vehicle, and data, with corresponding time stamp, on heading angle and velocity of the neighbouring road vehicle 10 IV having no active onboard.
- the data server 3 , 4 , 4 ′′ also acquiring global positioning data of at least the neighbouring road vehicle 10 IV having no active onboard sensors.
- the velocity of the neighbouring road vehicle 10 IV having no active onboard sensors may be used as a positioning anchor for the first road vehicle 10 .
- a neighbouring road vehicle 10 IV may be connected to the data server 3 , 4 , 4 ′′ via the other road vehicles 10 , 10 ′, 10 ′′, 10 ′′′ and be provided with adjusted global positioning data from the data server 3 , 4 , 4 ′′ using the arrangement and method describe above.
- the data server 3 , 4 , 4 ′′ may acquire data for the neighbouring road vehicle 10 IV having no active onboard sensors from onboard sensors 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g on at least two of the road vehicles 10 , 10 ′, 10 ′′, 10 ′′′.
- the data comprising unique vehicle identification data, e.g. license plate number, and data, with corresponding time stamp, on heading angle and velocity of the road vehicle 10 IV having no active onboard sensors.
- the data server may further acquire global positioning data for at least the neighbouring road vehicle 10 IV having no active onboard sensors. This data being processed in the data server 3 , 4 , 4 ′′′ together with the other data to calculate adjusted global positioning data for the identified road vehicle 10 IV having no active onboard sensors.
- the adjusted positioning data may be communicated to a positioning system 6 IV of the neighbouring road vehicle 10 IV having no active onboard sensors. This method may improve navigation performance where the positioning performance is poor and bring more accurate connected safety features to vehicles without ADAS sensors.
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Electromagnetism (AREA)
- Automation & Control Theory (AREA)
- Traffic Control Systems (AREA)
Abstract
Description
- The disclosure is related to a method and arrangement for improving global positioning performance of a road vehicle.
- Global positioning of an autonomous driving (AD) road vehicle is mainly based on positioning data such as Global Positioning System (GPS) coordinates. Such positioning data may not be very accurate and may differ from the actual global position of the road vehicle at a certain time. For many vehicles, and especially for AD vehicles, a more precise global positioning of the vehicle is critical and there is a need to develop approaches to address problems with inadequate global positioning accuracy.
- One approach is given by CN104502936, which discloses a positioning and navigation system comprising a combined positioning unit, an intelligent ranging unit, a cloud communication unit and a vehicle-mounted display unit. The combined positioning unit is used for realizing real-time positioning of the vehicle; the intelligent ranging unit is used for realizing calculation on the distance between the vehicle and a surrounding target; and the cloud communication unit is used for receiving data generated by the combined positioning unit and the intelligent ranging unit and for uploading the data to a cloud service centre. The cloud service centre carries out map labelling on navigation positioning data, and the labelling information is issued to the vehicle-mounted display unit.
- DE102012224110 discloses a method and system for determining positioning data of an object on a road. An environmental sensor system, e.g. camera, radar sensor, can be used to determine relative distances between an object whose absolute geographical position is known and an object to be located. The determined relative distances can serve as a filter basis, on the basis of which the positioning data of the object to be located can either be completely predetermined or, for example, specified in terms of tolerance. By the method an object can determine its absolute geographical position using the absolute geographical position of the other object and the relative distances. An object may also determine the position of another other object if its own absolute geographical position but not the corresponding absolute geographical position of the other object is available.
- In U.S. Pat. No. 9,933,268 is disclosed a digital map enhancement system for improving accuracy of pre-stored digital map data of a digital map to be utilized by a vehicle. The system determines a current position of the vehicle, and identifies, in the pre-stored digital map data, a mapped digital landmark representing a stationary landmark predicted to be in the vicinity of the current position of the vehicle, which mapped digital landmark includes a pre-stored position of the stationary landmark. The system detects the stationary landmark by one or more sensor devices on-board the vehicle, which are adapted for observing the surroundings of the vehicle, and determines a detected position of the stationary landmark based on the current position of the vehicle and the detection of the stationary landmark. The system updates the pre-stored position of the mapped digital landmark with the detected position of the stationary landmark.
- An object of the present invention is to provide a method for improving global positioning performance of a road vehicle using global positioning data and information from onboard sensors on the road vehicle and on at least two neighbouring road vehicles. Another objective is to provide an arrangement for improving global positioning performance of a road vehicle.
- The invention is defined by the appended independent claims. Embodiments are set forth in the appended dependent claims and in the figures.
- According to a first aspect there is provided a method for improving global positioning performance of a first road vehicle, the method comprising, by means of a data server: acquiring data from onboard sensors arranged on the first road vehicle and on at least two neighbouring road vehicles, the data comprising data on relative positions and data on heading angle and velocity of the road vehicles, and acquiring global positioning data of at least two of the road vehicles; processing the global positioning data, the data, with corresponding timestamp, acquired from the onboard sensors, and a motion model for each of the first road vehicle and the at least two neighbouring road vehicles, using a data fusion algorithm; calculating adjusted global positioning data for the first road vehicle, and communicating the adjusted global positioning data to a positioning system of the first road vehicle.
- A road vehicle may be a car, a truck, a bus etc. The first road vehicle and the at least two neighbouring road vehicles may be different types of road vehicles or be the same type of road vehicle, e.g. cars. The road vehicles may be autonomous driving (AD) vehicles or vehicles with advanced driving assistance systems (ADAS) for measuring vehicle information and information about the vehicle surroundings. At least one of the vehicles may be an autonomous driving (AD) vehicle and the other vehicles with advanced driving assistance systems (ADAS). All vehicles may be AD vehicles. All vehicles may be vehicles with ADAS. A vehicle provided with ADAS is here a vehicle provided with systems to help a driver in the driving process, e.g. through systems such as blind spot alerting, automatic lane centring, automatic braking, traffic warnings, lane departure warning system, automatic lighting, adaptive cruise control etc. AD vehicles are vehicles that are capable of sensing their environment and to navigate without human input. AD vehicles may, hence, be controlled without human interaction. AD vehicles could range from fully automated to semi-automated vehicles.
- The number of neighbouring vehicles used in the method should be at least two. The number of vehicles in the method may vary and may depend on different factors such as the number of onboard sensors on the vehicles, strength of sensor signals, distance to neighbouring vehicles etc. The road vehicles used by the method may form a wireless network.
- The onboard sensors may be arranged to detect environmental information associated with the road vehicle. Such sensors may e.g. detect a location of the vehicle, a velocity of the vehicle, an orientation of the vehicle, heading angle of the vehicle, and a status of surroundings of the vehicle.
- The at least two neighbouring road vehicles are located in relation to the first road vehicle in an area close enough such that onboard sensors on the respective road vehicle may detect at least one other vehicle. The size of such an area depends on the sensor set up on each road vehicle and the sensor coverage.
- The time stamp is the time at which an event is recorded by an onboard sensor.
- With a motion model for a road vehicle is here meant any vehicle motion model, e.g. a constant velocity model or a constant acceleration model.
- Each road vehicle may be provided with a data server communication unit for sending/receiving data to/from the data server.
- The global positioning data of a road vehicle may e.g. be Global Positioning System (GPS) coordinates. Such positioning data may not be very accurate and may differ from the actual global position at a certain time.
- The global positioning data received by the data server may be global positioning data for the first road vehicle and one or more neighbouring vehicles, or global positioning data for the at least two neighbouring vehicles only.
- With the data fusion algorithm desired parameters according to observations given at a present time and through a system model are estimated and predicted. Since the sensor data arrive at the data server at different rates with different communication delays, the sequential processing of sensor data may be computationally intensive. Therefore, a data fusion approach is proposed to deal with asynchronous sensor data, for example by using a multi-rate Kalman filter.
- In real situations, sensors provide object information in different sampling periods. In many cases the sampling times are asynchronous. Thus, it is needed to design a multi-rate estimator for each object dynamics to estimate object parameters, e.g. position, velocity, heading angle, etc. at the same sampling period. This may be done using an asynchronous data fusion algorithm.
- A positioning system of a vehicle is a system arranged to adjust the positioning of the vehicle on the road based on the received adjusted global positioning data.
- For many vehicles, especially AD vehicles, a more precise global positioning of the vehicle is critical. With the present method the global positioning performance of a road vehicle may be improved. Using relative distances between vehicles (pseudo-ranges) results in a more accurate global positioning compared to pseudo-ranges calculated with respect to GPS satellites. As all vehicles are located in approximately the same plane, this improves the global positioning accuracy of a vehicle. For AD and ADAS vehicles the accurate positioning needed is in the longitudinal and latitudinal direction and as the pseudo-range calculated in the method is in this plane the positioning accuracy is improved compared to when using GPS coordinates alone. The present method is a cooperative vehicle global positioning method and each road vehicle may be seen as a moving anchor in a wireless network. Data that each road vehicle gathers about other vehicles is used to improve the global positioning. By this method, vehicles provided with ADAS may contribute for a more accurate global positioning of (an) AD vehicle(s).
- The data server may be located in the first road vehicle.
- The data server may comprise a central data server.
- The data server could be a central data server, e.g. a cloud. The cloud may include different modules for communication; receiving and sending data, storing data, and processing of data.
- The data server may comprise a data server located in at least one of the road vehicles and/or a central data server.
- The data server could comprise a distributed data server with a data server arranged in at least one or more of the road vehicles, such that there may be a full vehicle-to-vehicle (V2V) communication. With full V2V communication the global positioning data is “younger” than if the information is sent to and processed in a central data server, i.e. a cloud.
- Alternatively, the data server could be a distributed data server comprising a central data server (cloud) and (a) data server(s) located in at least one of the road vehicles, thereby reducing the amount of communication with the central data server. Some functions of the data server could then be performed by the central server and some functions by (a) data server(s) located in at least one of the vehicles. If one vehicle loses connection with the central server there may be a possibility to indirectly connect to the central server via another vehicle used in the method.
- An onboard sensor may be selected from a group comprising radars, vision sensors and lidar sensors.
- At least one of the road vehicles may be an autonomous driving (AD) vehicle.
- At least one of the road vehicles may be a vehicle with advanced driving assistance systems (ADAS).
- The global positioning data processed by the data server may comprise the global positioning data of the first road vehicle.
- The global positioning data processed by the data server may consist of global positioning data of at least two of the neighbouring road vehicles, wherein the velocity of the road vehicles and the relative positions of the road vehicles may be used as positioning anchors for the first road vehicle when processing the data in the data server.
- Here the global positioning data of the first road vehicle is missing, which may be the case if the GPS connection of the first road vehicle is lost for some reason, e.g. when driving through a tunnel.
- A positioning anchor is a known object with respect to which the first road vehicle finds its position. For example, in a GPS system, the satellites are anchors. Anchors might be moving or stationary, their positions might be known or unknown.
- Global positioning data of one or more neighbouring road vehicles may be processed with the other data in the data server and adjusted global positioning data for at least one of the one or more neighbouring road vehicles may be calculated and communicated to a positioning system of the neighbouring road vehicle(s).
- Thereby, the global positioning of also such neighbouring road vehicles may be adjusted.
- The method may further comprise, by means of the data server, to acquire data for a neighbouring road vehicle having no active onboard sensors from onboard sensors on at least two of the road vehicles, the data comprising vehicle identification data and data on heading angle and velocity of the road vehicle having no active onboard sensors, and to acquire global positioning data of at least the neighbouring road vehicle having no active onboard sensors. When processing data in the data server, processing also the global positioning data and the data, with corresponding time stamp, acquired from the onboard sensors for the neighbouring road vehicle having no active onboard sensors, and using the velocity of the neighbouring road vehicle having no active onboard sensors as a positioning anchor for the first road vehicle.
- That a road vehicle does not have active onboard sensors is here meant that the vehicle is not provided with any onboard sensors or that the onboard sensors on the vehicle are not in use or not functioning.
- In this way neighbouring road vehicles having no active onboard sensors may contribute in the method of improving the global positioning of the first road vehicle.
- The velocity and heading angle for the road vehicle having no active onboard sensors may be obtained through odometry signals.
- Vehicle identification data for at least some of the other vehicles used in the method may be acquired by the data server together with the vehicle identification data of the vehicle having no active road sensors.
- The method may further comprise, by means of the data server, to acquire data for a neighbouring road vehicle having no active onboard sensors from onboard sensors on at least two of the road vehicles, the data comprising vehicle identification data and data on heading angle and velocity of the road vehicle having no active onboard sensors, and acquiring global positioning data of at least the neighbouring road vehicle having no active onboard sensors. When processing data in the data server, processing also the global positioning data and the data, with corresponding time stamp, acquired from the onboard sensors for the neighbouring road vehicle having no active onboard sensors. Adjusted global positioning data for the neighbouring road vehicle having no active onboard sensors may be calculated and communicated to a positioning system of the neighbouring road vehicle having no active onboard sensors.
- That a road vehicle does not have active onboard sensors is here meant that the vehicle is not provided with any onboard sensors or that the onboard sensors on the vehicle are not in use or not functioning.
- With this method, a road vehicle having no active onboard sensors but provided with positioning data sensor may be connected to the data server via the other road vehicles and be provided with adjusted positioning data from the data server.
- With this method, at a low cost, also road vehicles having no active onboard sensors may be provided with adjusted positioning data which may be used to adjust the spatial position of the road vehicle.
- This method would improve navigation performance where the positioning performance is poor and bring more accurate connected safety features to vehicles without onboard sensors.
- The velocity and heading angle for the road vehicle having no active onboard sensors may be obtained through odometry signals.
- Vehicle identification data for at least some of the other vehicles used in the method may be acquired by the data server together with the vehicle identification data of the vehicle having no active road sensors. This to make sure that the correct vehicle receives the adjusted global positioning data.
- The vehicle identification data for a road vehicle having no active onboard sensors may be the license plate number.
- The vehicle identification data of a vehicle without active onboard sensors need to be unique for that vehicle.
- Based on the adjusted global positioning data communicated to the positioning system of a road vehicle, the global position of a road vehicle may be adjusted.
- Such positioning adjustment is the spatial position of the vehicle in the longitudinal and latitudinal direction.
- According to a second aspect there is provided an arrangement for improving global positioning performance of a first road vehicle. The arrangement comprises a data server communication unit for communication with a data server, onboard sensors arranged on the first road vehicle and being arranged to determine data on relative positions and data on heading angle and velocity of one or more neighbouring road vehicles, the data server communication unit further being arranged to send the determined data, with corresponding time stamp, to the data server. A global positioning sensor is arranged on the first road vehicle, the data server communication unit further being arranged to send global positioning data of the first road vehicle to the data server, and a positioning system is arranged on the first road vehicle. The data server communication unit further is arranged to receive to the positioning system of the first road vehicle adjusted global positioning data for the first road vehicle, the adjusted global positioning data obtained using a data fusion algorithm, the data fusion algorithm arranged to process global positioning data from the first road vehicle and at least one or more neighbouring road vehicles, a motion model of each road vehicle, data on relative positions of each road vehicle, and data on heading angle and velocity of the road vehicles, to calculate the adjusted global positioning data for the first road vehicle.
-
FIG. 1 illustrates an arrangement for improving global positioning performance of a first road vehicle using global positioning data and information from onboard sensors on the first road vehicle and on at least two neighbouring road vehicles. -
FIG. 2 schematically illustrates method steps of a method for improving global positioning performance of a first road vehicle. - Global positioning of an autonomous driving (AD) road vehicle is mainly based on positioning data such as Global Positioning System (GPS) coordinates, which may not be very accurate and may differ from the actual global position of the road vehicle at a certain time. In
FIG. 1 is shown an arrangement for improving global positioning performance of aroad vehicle 10 using global positioning data and information fromonboard sensors road vehicle 10 and on at least two neighbouringroad vehicles 10′, 10″, 10′″. InFIG. 2 is schematically illustrated a method for improving the global positioning performance of a road vehicle. - As seen in
FIG. 1 the arrangement comprises afirst road vehicle 10 and at least two neighbouringroad vehicles 10′, 10″, 10′″, a data server 3, 4, 4″ andonboard sensors first road vehicle 10 and on the at least two neighbouringroad vehicles 10′, 10″, 10′″. Theroad vehicles - The
onboard sensors road vehicles onboard sensors 2 a. 2 b, 2 c, 2 d, 2 e, 2 f, 2 g on avehicle - The data is sent, with corresponding time stamp, to the data server 3, 4, 4″ via a data
server communication unit first road vehicle 10. The data server may alternatively be a central data server 3, i.e. a cloud. In yet an alternative, the data server may comprise one or more distributed data servers 4, 4″ located in at least one of theroad vehicles -
Global positioning sensors road vehicles road vehicles server communication unit first road vehicle 10 and of one or more of the neighbouringroad vehicles 10′, 10″, 10′″. Alternatively, the global positioning data may consist of global positioning data of at least two of the neighbouringroad vehicles 10′, 10″, 10′″ and no data for thefirst road vehicle 10. - Having acquired the data from the
onboard sensors global positioning sensors first road vehicle 10 and the at least twoneighbouring vehicles 10′, 10″, 10′″ using a data fusion algorithm and calculate an adjusted global positioning data for thefirst road vehicle 10. The adjusted global positioning data may be communicated to apositioning system 6 of thefirst road vehicle 10. Thepositioning system 6 may be arranged to adjust the global positioning of thevehicle 10 on the road, improving the global positioning performance of the first road vehicle. Data that eachroad vehicle first road vehicle 10 and a more accurate global positioning of thefirst road vehicle 10 may be obtained. - In the method shown in
FIG. 2 , the first step is to, by means of the data server 3, 4, 4″, acquiredata 101 from theonboard sensors road vehicles road vehicles processes 102 the data comprising the global positioning data, the data, with corresponding timestamp, acquired from theonboard sensors first road vehicle 10 and the at least two neighbouringroad vehicles 10′, 10″, 10′″. In the next step adjusted global positioning data for thefirst road vehicle 10 is calculated 103, and thereafter the adjusted global positioning data is communicated 104 to thepositioning system 6 of thefirst road vehicle 10. Then, the global position of the first road vehicle may be adjusted 105 to a more accurate global position. - In some cases, global positioning data of the
first road vehicle 10 may be missing. This situation may for example occur if the GPS connection of thefirst road vehicle 10 is lost for some reason, e.g. when driving through a tunnel. The global positioning data sent to the data server 3, 4, 4″ then consists of global positioning data of at least two of the neighbouringvehicles 10′. 10″, 10′″. The velocity of theroad vehicles first road vehicle 10 when processing the data in the data server 3, 4, 4″. - Also, the global positioning of a neighbouring
road vehicle 10′ may be adjusted with this arrangement and method. Global positioning data of the one or more neighbouringroad vehicles 10′ sent to the data server 3, 4, 4″ may be processed together with the other data and adjusted global positioning data for the neighbouring road vehicle(s) 10′ communicated to (a) positioning system(s) 6′ of the neighbouring road vehicle(s) 10′. - Additionally, road vehicles having no onboard sensors, or such sensors being not in use or not functioning, may contribute in the method of improving the global positioning performance of the
first road vehicle 10. In such case, the data server 3, 4, 4″ acquires data for a neighbouringroad vehicle 10 IV having no active onboard sensors from onboard sensor(s) 2 a, 2 b, 2 c, 2 d, 2 e, 2 f, 2 g on at least two of theroad vehicles road vehicle 10 IV having no active onboard. The data server 3, 4, 4″ also acquiring global positioning data of at least the neighbouringroad vehicle 10 IV having no active onboard sensors. When processing also this data in the data server 3, 4, 4″ the velocity of the neighbouringroad vehicle 10 IV having no active onboard sensors may be used as a positioning anchor for thefirst road vehicle 10. - If a neighbouring
road vehicle 10 IV does not have any onboard sensors or such sensors being not in use or not functioning, such avehicle 10 IV may be connected to the data server 3, 4, 4″ via theother road vehicles road vehicle 10 IV having no active onboard sensors fromonboard sensors road vehicles road vehicle 10 IV having no active onboard sensors. The data server may further acquire global positioning data for at least the neighbouringroad vehicle 10 IV having no active onboard sensors. This data being processed in the data server 3, 4, 4′″ together with the other data to calculate adjusted global positioning data for the identifiedroad vehicle 10 IV having no active onboard sensors. The adjusted positioning data may be communicated to apositioning system 6 IV of the neighbouringroad vehicle 10 IV having no active onboard sensors. This method may improve navigation performance where the positioning performance is poor and bring more accurate connected safety features to vehicles without ADAS sensors.
Claims (15)
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP18178298.8 | 2018-06-18 | ||
EP18178298.8A EP3584607B1 (en) | 2018-06-18 | 2018-06-18 | Method and arrangement for improving global positioning performance of a road vehicle |
EP18178298 | 2018-06-18 |
Publications (2)
Publication Number | Publication Date |
---|---|
US20190383950A1 true US20190383950A1 (en) | 2019-12-19 |
US11550066B2 US11550066B2 (en) | 2023-01-10 |
Family
ID=62705501
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US16/444,221 Active 2039-11-21 US11550066B2 (en) | 2018-06-18 | 2019-06-18 | Method and arrangement for improving global positioning performance of a road vehicle |
Country Status (3)
Country | Link |
---|---|
US (1) | US11550066B2 (en) |
EP (1) | EP3584607B1 (en) |
CN (1) | CN110618423A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPWO2022130619A1 (en) * | 2020-12-18 | 2022-06-23 |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114114369B (en) * | 2022-01-27 | 2022-07-15 | 智道网联科技(北京)有限公司 | Autonomous vehicle positioning method and apparatus, electronic device, and storage medium |
CN115825901B (en) * | 2023-02-21 | 2023-04-28 | 南京楚航科技有限公司 | Vehicle-mounted sensor perception performance evaluation truth value system |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100164789A1 (en) * | 2008-12-30 | 2010-07-01 | Gm Global Technology Operations, Inc. | Measurement Level Integration of GPS and Other Range and Bearing Measurement-Capable Sensors for Ubiquitous Positioning Capability |
US20170307763A1 (en) * | 2016-04-26 | 2017-10-26 | Uber Technologies, Inc. | Road registration differential gps |
US20180232947A1 (en) * | 2017-02-11 | 2018-08-16 | Vayavision, Ltd. | Method and system for generating multidimensional maps of a scene using a plurality of sensors of various types |
US20190382003A1 (en) * | 2018-06-13 | 2019-12-19 | Toyota Jidosha Kabushiki Kaisha | Collision avoidance for a connected vehicle based on a digital behavioral twin |
Family Cites Families (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9052207B2 (en) * | 2009-10-22 | 2015-06-09 | Tomtom Polska Sp. Z O.O. | System and method for vehicle navigation using lateral offsets |
US20110153266A1 (en) * | 2009-12-23 | 2011-06-23 | Regents Of The University Of Minnesota | Augmented vehicle location system |
US9581997B1 (en) * | 2011-04-22 | 2017-02-28 | Angel A. Penilla | Method and system for cloud-based communication for automatic driverless movement |
KR101231534B1 (en) * | 2011-10-17 | 2013-02-07 | 현대자동차주식회사 | A method and system to improve accuracy in differential global positioning system using vehicle to vehicle |
DE102012224110A1 (en) | 2012-12-20 | 2014-06-26 | Continental Teves Ag & Co. Ohg | Method for determining position data of objects e.g. vehicle and traffic light, on road, involves filtering data of vehicle based on detected distance between vehicle and another vehicle for determining data of latter vehicle on road |
US9329597B2 (en) * | 2014-01-17 | 2016-05-03 | Knightscope, Inc. | Autonomous data machines and systems |
KR102286673B1 (en) * | 2014-04-09 | 2021-08-05 | 콘티넨탈 테베스 아게 운트 코. 오하게 | Position correction of a vehicle by referencing to objects in the surroundings |
CN104502936B (en) | 2014-11-24 | 2017-05-10 | 福建爱特点信息科技有限公司 | High-precision positioning and navigation system |
EP3032221B1 (en) | 2014-12-09 | 2022-03-30 | Volvo Car Corporation | Method and system for improving accuracy of digital map data utilized by a vehicle |
EP3130945B1 (en) * | 2015-08-11 | 2018-05-02 | Continental Automotive GmbH | System and method for precision vehicle positioning |
CN105865461B (en) * | 2016-04-05 | 2019-07-12 | 武汉理工大学 | A kind of car position system and method based on Multi-sensor Fusion algorithm |
WO2017189361A1 (en) * | 2016-04-29 | 2017-11-02 | Pcms Holdings, Inc. | System and method for calibration of vehicle sensors assisted by inter-vehicle communication |
JP2019532292A (en) * | 2016-09-29 | 2019-11-07 | ザ・チャールズ・スターク・ドレイパー・ラボラトリー・インコーポレイテッド | Autonomous vehicle with vehicle location |
US10091791B2 (en) * | 2016-12-02 | 2018-10-02 | Qualcomm Incorporated | Vehicle positioning by signaling line-of-sight (LOS) vehicle information |
DE102016224329A1 (en) * | 2016-12-07 | 2018-06-07 | Robert Bosch Gmbh | Method and system for locating a vehicle |
EP3538929B1 (en) * | 2017-03-20 | 2021-09-08 | Google LLC | Systems and methods of determining an improved user location using real world map and sensor data |
CN107315413B (en) * | 2017-07-12 | 2020-07-21 | 北京航空航天大学 | Multi-vehicle cooperative positioning algorithm considering relative positions between vehicles in vehicle-vehicle communication environment |
CN107728175A (en) * | 2017-09-26 | 2018-02-23 | 南京航空航天大学 | The automatic driving vehicle navigation and positioning accuracy antidote merged based on GNSS and VO |
-
2018
- 2018-06-18 EP EP18178298.8A patent/EP3584607B1/en active Active
-
2019
- 2019-06-18 CN CN201910526022.4A patent/CN110618423A/en active Pending
- 2019-06-18 US US16/444,221 patent/US11550066B2/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100164789A1 (en) * | 2008-12-30 | 2010-07-01 | Gm Global Technology Operations, Inc. | Measurement Level Integration of GPS and Other Range and Bearing Measurement-Capable Sensors for Ubiquitous Positioning Capability |
US20170307763A1 (en) * | 2016-04-26 | 2017-10-26 | Uber Technologies, Inc. | Road registration differential gps |
US20180232947A1 (en) * | 2017-02-11 | 2018-08-16 | Vayavision, Ltd. | Method and system for generating multidimensional maps of a scene using a plurality of sensors of various types |
US20190382003A1 (en) * | 2018-06-13 | 2019-12-19 | Toyota Jidosha Kabushiki Kaisha | Collision avoidance for a connected vehicle based on a digital behavioral twin |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPWO2022130619A1 (en) * | 2020-12-18 | 2022-06-23 | ||
WO2022130619A1 (en) * | 2020-12-18 | 2022-06-23 | 三菱電機株式会社 | Correction data generation device, vehicle-mounted device, correction data generation method, error correction method, correction data generation program, and error correction program |
JP7209918B2 (en) | 2020-12-18 | 2023-01-20 | 三菱電機株式会社 | Correction data generation device, correction data generation method, and correction data generation program |
Also Published As
Publication number | Publication date |
---|---|
EP3584607B1 (en) | 2023-03-01 |
CN110618423A (en) | 2019-12-27 |
US11550066B2 (en) | 2023-01-10 |
EP3584607A1 (en) | 2019-12-25 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
EP3644294B1 (en) | Vehicle information storage method, vehicle travel control method, and vehicle information storage device | |
US10210406B2 (en) | System and method of simultaneously generating a multiple lane map and localizing a vehicle in the generated map | |
CN110626343B (en) | Method for automatically guiding a following vehicle laterally in a vehicle train | |
US9162682B2 (en) | Method and device for determining the speed and/or position of a vehicle | |
US20190077459A1 (en) | Vehicle control device, vehicle control method, and recording medium | |
EP3745376B1 (en) | Method and system for determining driving assisting data | |
WO2019161134A1 (en) | Lane marking localization | |
US11740093B2 (en) | Lane marking localization and fusion | |
US11550066B2 (en) | Method and arrangement for improving global positioning performance of a road vehicle | |
JP2019532292A (en) | Autonomous vehicle with vehicle location | |
US20070043502A1 (en) | System for and method of detecting a collision and predicting a vehicle path | |
US20190293435A1 (en) | Host vehicle position estimation device | |
US11585945B2 (en) | Method for the satellite-supported determination of a position of a vehicle | |
CN112477860A (en) | Vehicle control device | |
US11538335B2 (en) | Traffic control system for automatic driving vehicle | |
CN109795500B (en) | Vehicle control device, vehicle control method, and storage medium | |
US11195027B2 (en) | Automated crowd sourcing of road environment information | |
US20210061270A1 (en) | Method and apparatus for method for real time lateral control and steering actuation assessment | |
CN110893845A (en) | Method and apparatus for diagonal lane detection | |
US20220292847A1 (en) | Drive assist device, drive assist method, and program | |
US20240140438A1 (en) | Perception blockage prediction and supervision for performing information cloud localization | |
US20240124060A1 (en) | A method for determining whether an automatic collision avoidance steering maneuver should be executed or not | |
US20230166761A1 (en) | Method and system for estimation of an operational design domain boundary | |
US20230408264A1 (en) | Lane marking localization and fusion | |
US20220307858A1 (en) | Vehicle position estimation device, vehicle position estimation method, and non-transitory recording medium |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: ZENUITY AB, SWEDEN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:BAGHERI, TOKTAM;REEL/FRAME:049504/0008 Effective date: 20190611 |
|
FEPP | Fee payment procedure |
Free format text: ENTITY STATUS SET TO UNDISCOUNTED (ORIGINAL EVENT CODE: BIG.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NON FINAL ACTION MAILED |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: RESPONSE TO NON-FINAL OFFICE ACTION ENTERED AND FORWARDED TO EXAMINER |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: FINAL REJECTION MAILED |
|
AS | Assignment |
Owner name: ZENUITY AB, SWEDEN Free format text: CHANGE OF ADDRESS;ASSIGNOR:ZENUITY AB;REEL/FRAME:058777/0600 Effective date: 20201116 |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: RESPONSE AFTER FINAL ACTION FORWARDED TO EXAMINER |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: ADVISORY ACTION MAILED |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NON FINAL ACTION MAILED |
|
STCT | Information on status: administrative procedure adjustment |
Free format text: PROSECUTION SUSPENDED |
|
STCT | Information on status: administrative procedure adjustment |
Free format text: PROSECUTION SUSPENDED |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NON FINAL ACTION MAILED |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: RESPONSE TO NON-FINAL OFFICE ACTION ENTERED AND FORWARDED TO EXAMINER |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NOTICE OF ALLOWANCE MAILED -- APPLICATION RECEIVED IN OFFICE OF PUBLICATIONS |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: PUBLICATIONS -- ISSUE FEE PAYMENT VERIFIED |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |